This disclosure relates to data processing.
ARM Fast Model™ system represents an example of a software modelling system for simulating multiple systems IP cores or blocks integrated in a system or subsystem. Here such an “IP” core or block may be, for example, a reusable unit of circuitry layout, typically for use in an integrated circuit, having a design which is the intellectual property (IP) of one party. But the term may be used more generally, for example, for blocks of integrated circuitry layout which can be assembled together to provide a composite function.
The Fast Model system allows a customer (for example, a manufacturer which intends to fabricate a physical circuit according to the design being modelled) to run a simulation involving a whole software stack as early as system IPs' specification is just ready. An example relates to the modelling of graphics processing units (GPUs) modelling and verification, which has previously been difficult because 3D (three dimensional) graphical rendering simulation for GPU verification can be very slow.
With the Fast Model or similar systems, hardware IP interfaces can be defined by code such as so-called “LISA+” code and easily visualized and combined to generate a complete subsystem. GPU architecture is evolving quickly, and it tends to use large numbers of unified scalar cores to solve parallel data stream processing problems. Compared with GPU, typically a CPU (central processing unit) has fewer cores, but a single CPU core can be more complicated than a single GPU core, for example having a deeper pipeline and/or bigger caches. For historical reasons, the GPU can tend to be treated as a peripheral device in a computer architecture based around a CPU. Therefore, in whole system simulation, typically a CPU is used to simulate all devices including 3D rendering using a GPU, but the significant architecture level difference between CPUs and GPUs makes fast GPU simulation difficult. Also, the increasing display resolution in mobile systems (as an example of the use of such a modelled GPU) is demanding even higher computation resources for a simulation environment.